Financial Due Diligence Prep for Forensic Accountants with ACL Analytics
The Problem
Quality-of-earnings work for Fraud Investigation targets starts with 18 months of trial balances and a dozen schedules that need normalization before any adjustment can be proposed.
What We Build in ACL Analytics
AI standardizes TB data across periods, builds the QoE model, identifies add-backs with source-document evidence, and drafts the data-book — senior analysts focus on judgment calls, not reformatting. Purpose-built for teams running ACL Analytics — uses the native API or agent integration so nothing leaves the system of record.
ACL Analytics Integration Approach
Audit your ACL Analytics configuration
We map the specific ACL Analytics objects, custom fields, and workflows the automation needs to touch for your fraud investigation practice.
Build on the ACL Analytics API or agent
Integration happens inside ACL Analytics — no data leaves the system, no parallel tool for your team to learn, no license changes.
Human-in-the-loop handoff
Every automation routes exceptions back to a human in ACL Analytics with enough context to act — AI handles the 80%, your team owns the judgment calls.
See this running in your ACL Analytics instance
30-minute call. We'll look at your actual ACL Analytics setup and show exactly how this workflow fits.